Ignite Creation Date:
2025-12-24 @ 2:11 PM
Ignite Modification Date:
2025-12-27 @ 9:46 PM
Study NCT ID:
NCT04256395
Status:
COMPLETED
Last Update Posted:
2020-07-07
First Post:
2020-02-01
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Efficacy of a Self-test and Self-alert Mobile Applet in Detecting Susceptible Infection of COVID-19
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D009164', 'term': 'Mycobacterium Infections'}], 'ancestors': [{'id': 'D000193', 'term': 'Actinomycetales Infections'}, {'id': 'D016908', 'term': 'Gram-Positive Bacterial Infections'}, {'id': 'D001424', 'term': 'Bacterial Infections'}, {'id': 'D001423', 'term': 'Bacterial Infections and Mycoses'}, {'id': 'D007239', 'term': 'Infections'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 102456}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-02-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2020-07', 'completionDateStruct': {'date': '2020-07-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2020-07-05', 'studyFirstSubmitDate': '2020-02-01', 'studyFirstSubmitQcDate': '2020-02-03', 'lastUpdatePostDateStruct': {'date': '2020-07-07', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-02-05', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-07-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'positive number diagnosed by national guideline in the evaluated population', 'timeFrame': '5 months', 'description': 'after the end of this study, investigators calculate and sum up the total evaluated population and positively diagnosed population, then check the ROC of this system, finally to calculate the sensitivity and accuracy of this self-test and self-alert system'}], 'secondaryOutcomes': [{'measure': 'distribution map of evaluated people', 'timeFrame': '5 month', 'description': 'after the end of this study, investigators calculate the proportion and distribution of evaluated people with normal and abnormal scores'}, {'measure': 'Effect of medical guidance by designated feedback questionnaire', 'timeFrame': '5 month', 'description': 'after the end of this study, investigators sent the feedback inform to every evaluated people and collect and analysis the response to find out whether this applet can help them in the following surveillance or medical treatment. And how it works.'}, {'measure': 'mental scale of relief the mental anxiety and avoid unnecessary outpatient', 'timeFrame': '5 month', 'description': 'after the end of this study, investigators sent the designated mental scale including anxiety, and collect the response and draw the conclusion.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['registry study', 'novel coronavirus（COVID-19）', 'mobile internet survey'], 'conditions': ['Susceptibility to Viral and Mycobacterial Infection']}, 'descriptionModule': {'briefSummary': 'The "COVID-19 infection self-test and alert system" (hereinafter referred to as "COVID-19 self-test applet") jointly developed by Beijing Tsinghua Changgung Hospital, Institute for precision medicine, artificial intelligence of Tsinghua University was launched on February 1，2020. Residents , according to their actual healthy situation, after answering questions online, the system will conduct intelligent analysis, make disease risk assessment and give healthcare and medical guidance. Based on the Internet population survey, and referring to the diagnosis and screening standards of the National Health Commission of the People\'s Republic of China, investigators carried out the mobile applet of Internet survey and registry study for the Internet accessible identifiable population, so as to screen the suspected population and guide the medical treatment.', 'detailedDescription': 'The "COVID-19 infection self-test and alert system" (hereinafter referred to as "COVID-19 self-test applet") jointly developed by Beijing Tsinghua Changgung Hospital, Institute for precision medicine, artificial intelligence of Tsinghua University was launched on February 1，2020. This survey was also advocated by Chinese Medical Doctor Association. Residents , or even oversea Chinese people，according to their actual healthy situation, after answering questions online, the system will conduct intelligent analysis, make disease risk assessment and give healthcare and medical guidance. Based on the Internet population survey, and referring to the diagnosis and screening standards of the National Health Commission of the People\'s Republic of China, investigators carried out the mobile applet of Internet survey and registry study for the Internet accessible identifiable population, so as to screen the suspected population and guide the medical treatment.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Most people including healthy or susceptible patients or diagnosed patients will be enrolled. People whoever worry about his heath status relating with infection of COVID-19 at present can register and answer the question and get a score for risk evaluation. If a high risk achieved, the applet will guide the interviewer for further medical diagnosis and treatment.', 'eligibilityCriteria': 'Inclusion Criteria:\n\n* people who lived in or out of China at present and threatened by the infection and spread of COVID-19\n\n * without gender and age restriction\n * people who have concerns of his health\n * voluntary completion of the self-test and evaluation.\n\nExclusion Criteria:\n\n* people who are not internet accessible or can not use this Mobile Applet.\n* people who can not recognize the questionnaire.'}, 'identificationModule': {'nctId': 'NCT04256395', 'acronym': 'COVID-19', 'briefTitle': 'Efficacy of a Self-test and Self-alert Mobile Applet in Detecting Susceptible Infection of COVID-19', 'organization': {'class': 'OTHER', 'fullName': 'Beijing Tsinghua Chang Gung Hospital'}, 'officialTitle': 'Registry Study on the Efficacy of a Self-test and Self-alert Applet in Detecting Susceptible Infection of COVID-19 --a Population Based Mobile Internet Survey', 'orgStudyIdInfo': {'id': 'RWS-BTCH-002'}}, 'armsInterventionsModule': {'interventions': [{'name': 'mobile internet survey on self-test', 'type': 'OTHER', 'description': '1\\. make a questionnaire, the content of which refers to the new coronavirus diagnosis and treatment guidelines released by the National Health Commission; 2. develop the mobile applet and carry out internet propagation; 3. background data could be identified according to computer technology, de duplication and de privacy; 4. once registered, the applet can automatically remind the self-test twice a day, and encourage to adhere to 14 days; 5. automatically compare with the standards and highly suspected population could be given medical guidance and encouraged to go to the fever clinic of the designated hospital for definite diagnosis.'}]}, 'contactsLocationsModule': {'locations': [{'zip': '102218', 'city': 'Beijing', 'state': 'Beijing Municipality', 'country': 'China', 'facility': 'Beijing Tsinghua Changgung Hospital', 'geoPoint': {'lat': 39.9075, 'lon': 116.39723}}], 'overallOfficials': [{'name': 'Jiahong Dong, M.D', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Beijing Tsinghua Changgeng Hospital'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Beijing Tsinghua Chang Gung Hospital', 'class': 'OTHER'}, 'collaborators': [{'name': 'Institute for precision medicine of Tsinghua University', 'class': 'UNKNOWN'}, {'name': 'Institute for artificial intelligent of Tsinghua University', 'class': 'UNKNOWN'}, {'name': 'Chinese Medical Doctor Association', 'class': 'OTHER'}, {'name': 'Institute for network behavior of Tsinghua University', 'class': 'UNKNOWN'}, {'name': 'school of clinical medicine of Tsinghua University', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR'}}}}